Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration

Nuwan Ganganath, Jing V. Wang, Xinzhi Xu, Chi-Tsun Cheng, Chi K. Tse

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

After a blackout, it is essential to restore the blackout area rapidly to minimize possible losses. In parallel restoration, the blackout area is first partitioned into several subsystems, which will then be restored in parallel to accelerate the restoration process. In order to ensure restoration reliability, each subsystem should have enough generation power and satisfy a set of constraints before triggering the parallel restoration process. This paper models this as a constrained optimization problem and proposes a partitioning strategy to solve it in three steps. In the first step, some existing methods and expert knowledge are used for initialization of the partitioning process. The second step ensures the satisfaction of modeled constraints. The third step operates greedily to find suitable partitions for parallel restoration. The proposed strategy is implemented and evaluated on IEEE 39- and 118-bus power systems. Evaluation results show that it provides adequate subsystems for parallel restoration. Unlike some existing partitioning strategies, the proposed strategy can be used to partition a power system into multiple subsystems in a single execution.

Original languageEnglish
Pages (from-to)3325-3333
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Volume14
Issue number8
DOIs
Publication statusPublished - Aug 2018

Cite this

Ganganath, Nuwan ; Wang, Jing V. ; Xu, Xinzhi ; Cheng, Chi-Tsun ; Tse, Chi K. / Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration. In: IEEE Transactions on Industrial Informatics. 2018 ; Vol. 14, No. 8. pp. 3325-3333.
@article{1a13ecca842b465aa2e011b41e036253,
title = "Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration",
abstract = "After a blackout, it is essential to restore the blackout area rapidly to minimize possible losses. In parallel restoration, the blackout area is first partitioned into several subsystems, which will then be restored in parallel to accelerate the restoration process. In order to ensure restoration reliability, each subsystem should have enough generation power and satisfy a set of constraints before triggering the parallel restoration process. This paper models this as a constrained optimization problem and proposes a partitioning strategy to solve it in three steps. In the first step, some existing methods and expert knowledge are used for initialization of the partitioning process. The second step ensures the satisfaction of modeled constraints. The third step operates greedily to find suitable partitions for parallel restoration. The proposed strategy is implemented and evaluated on IEEE 39- and 118-bus power systems. Evaluation results show that it provides adequate subsystems for parallel restoration. Unlike some existing partitioning strategies, the proposed strategy can be used to partition a power system into multiple subsystems in a single execution.",
keywords = "Agglomerative clustering, network partitioning, parallel restoration, power systems, sectionalizing, smart grid, STRATEGIES, METHODOLOGY",
author = "Nuwan Ganganath and Wang, {Jing V.} and Xinzhi Xu and Chi-Tsun Cheng and Tse, {Chi K.}",
year = "2018",
month = "8",
doi = "10.1109/TII.2017.2780167",
language = "English",
volume = "14",
pages = "3325--3333",
journal = "IEEE Transactions on Industrial Informatics",
issn = "1551-3203",
publisher = "IEEE, Institute of Electrical and Electronics Engineers",
number = "8",

}

Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration. / Ganganath, Nuwan; Wang, Jing V.; Xu, Xinzhi; Cheng, Chi-Tsun; Tse, Chi K.

In: IEEE Transactions on Industrial Informatics, Vol. 14, No. 8, 08.2018, p. 3325-3333.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration

AU - Ganganath, Nuwan

AU - Wang, Jing V.

AU - Xu, Xinzhi

AU - Cheng, Chi-Tsun

AU - Tse, Chi K.

PY - 2018/8

Y1 - 2018/8

N2 - After a blackout, it is essential to restore the blackout area rapidly to minimize possible losses. In parallel restoration, the blackout area is first partitioned into several subsystems, which will then be restored in parallel to accelerate the restoration process. In order to ensure restoration reliability, each subsystem should have enough generation power and satisfy a set of constraints before triggering the parallel restoration process. This paper models this as a constrained optimization problem and proposes a partitioning strategy to solve it in three steps. In the first step, some existing methods and expert knowledge are used for initialization of the partitioning process. The second step ensures the satisfaction of modeled constraints. The third step operates greedily to find suitable partitions for parallel restoration. The proposed strategy is implemented and evaluated on IEEE 39- and 118-bus power systems. Evaluation results show that it provides adequate subsystems for parallel restoration. Unlike some existing partitioning strategies, the proposed strategy can be used to partition a power system into multiple subsystems in a single execution.

AB - After a blackout, it is essential to restore the blackout area rapidly to minimize possible losses. In parallel restoration, the blackout area is first partitioned into several subsystems, which will then be restored in parallel to accelerate the restoration process. In order to ensure restoration reliability, each subsystem should have enough generation power and satisfy a set of constraints before triggering the parallel restoration process. This paper models this as a constrained optimization problem and proposes a partitioning strategy to solve it in three steps. In the first step, some existing methods and expert knowledge are used for initialization of the partitioning process. The second step ensures the satisfaction of modeled constraints. The third step operates greedily to find suitable partitions for parallel restoration. The proposed strategy is implemented and evaluated on IEEE 39- and 118-bus power systems. Evaluation results show that it provides adequate subsystems for parallel restoration. Unlike some existing partitioning strategies, the proposed strategy can be used to partition a power system into multiple subsystems in a single execution.

KW - Agglomerative clustering

KW - network partitioning

KW - parallel restoration

KW - power systems

KW - sectionalizing

KW - smart grid

KW - STRATEGIES

KW - METHODOLOGY

U2 - 10.1109/TII.2017.2780167

DO - 10.1109/TII.2017.2780167

M3 - Article

VL - 14

SP - 3325

EP - 3333

JO - IEEE Transactions on Industrial Informatics

JF - IEEE Transactions on Industrial Informatics

SN - 1551-3203

IS - 8

ER -